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.FAF Context

.FAF Context

by Wolfe-Jam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

faf_init

Initialize a project.faf file to make any project instantly AI-readable, returning its location and starting score.

Instructions

Create a project.faf for a project, making it instantly AI-readable. Returns the new file location and starting score. Accepts a path or bare project name (e.g. ~/Projects/my-app, my-app) and omitting it uses the current directory.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "faf_init"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathNoProject path or name. Smart resolution: "my-app" finds ~/Projects/my-app OR ~/Code/my-app. Full paths like ~/Projects/app or /Users/me/code/app work too. Omit to use current directory.
forceNoOverwrite existing project.faf if it exists

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.1

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=false and destructiveHint=false, so the description is not required to restate these. It adds value by explaining the side effect (creating a file) and the return values (file location and starting score). However, it does not mention behavior when the file already exists without the 'force' parameter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise (three sentences) and front-loads the main purpose. Each sentence provides relevant information, though space could be saved by merging the last two sentences. Overall, it is appropriately sized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (2 optional parameters, no output schema), the description covers the essential aspects: purpose, return values, and parameter usage. It does not mention error handling or edge cases, but these are minor gaps for such a simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds significant semantic detail beyond the schema, especially for the 'path' parameter (smart resolution rules, examples). For 'force', the description is sufficient. The added context helps the agent understand parameter behavior better than the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool creates a 'project.faf' file for a project, making it AI-readable. The verb 'Create' is specific to the resource, and the description differentiates from sibling tools like 'faf_score' or 'faf_sync' by focusing on initialization.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear guidance on when to use the tool: to create a project.faf. It explains acceptable inputs (path, bare name, omit) with examples, but does not explicitly mention when not to use it or suggest alternatives, leaving some ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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